From Lumen to Myocardium With Artificial Intelligence: A Clinician's Guide to Comprehensive Cardiac CT

Area of Science:

• Cardiovascular Imaging
• Radiology
• Artificial Intelligence in Medicine

Background:

• Traditional coronary artery disease assessment relies on stenosis severity, which inadequately reflects ischemic burden, plaque vulnerability, or myocardial health.
• This limitation leads to unnecessary invasive procedures and delayed preventive treatments.
• Cardiac computed tomography (CT) has emerged as a powerful noninvasive tool to overcome these limitations.

Purpose of the Study:

• To review current evidence on advanced cardiac CT applications for coronary artery disease.
• To provide practical guidance for clinicians integrating CT into patient management.
• To highlight the role of artificial intelligence (AI) in enhancing CT's capabilities.

Main Methods:

• Synthesis of current scientific literature and clinical trial data on coronary CT angiography (CCTA).
• Review of studies evaluating CT-derived fractional flow reserve (CT-FFR) and quantitative plaque analysis.
• Exploration of emerging CT applications like extracellular volume (ECV) quantification.

Main Results:

• High-quality CCTA is foundational for anatomical assessment and complex revascularization planning, with trials showing reduced invasive procedures.
• CT-FFR enhances diagnostic specificity and guides revascularization, though prognostic data are evolving.
• Quantitative plaque analysis, including low-attenuation and total plaque volume, strongly predicts myocardial infarction and mortality, even in nonobstructive disease.
• Emerging CT applications like ECV show promise in detecting diffuse fibrosis and cardiac amyloidosis.

Conclusions:

• Cardiac CT provides a comprehensive, noninvasive platform for coronary artery disease assessment, moving beyond simple stenosis evaluation.
• AI integration is crucial for maximizing the potential of advanced CT techniques.
• CT offers significant value in guiding revascularization, predicting adverse events, and diagnosing conditions like cardiac amyloidosis.